Karol Hausman

収録論文 53本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• π0.7: 操縦可能な汎用ロボット基盤モデルと創発的能力
  VLA2026/4/1

  多様なコンテキスト条件付けを用いて、未見環境での言語指示追従やゼロショットの身体汎化を実現するロボット基盤モデルπ0.7を提案した。

• π*0.6：経験から学ぶVLA
  VLA2025/11/1

  実世界での経験と人間の修正を活用した強化学習手法RECAPにより、洗濯物畳みや箱組み立て、エスプレッソ抽出などのタスクを高成功率で実行できる汎用VLAモデルπ*0.6を開発した。

• π0.5: オープンワールド汎化を実現する視覚-言語-行動モデル
  VLA2025/4/1

  異種タスクの共同学習により、未知の家庭環境でもキッチンや寝室の掃除などの長期的で器用な操作を実行できるVLAモデルπ0.5を提案した。

• π0: 汎用ロボット制御のための視覚-言語-行動フローモデル
  VLA2024/10/1

  事前学習済み視覚言語モデルにフローマッチングを組み合わせ、多様なロボットの大規模データで訓練することで、洗濯物畳みや箱組み立てなどの器用なタスクをゼロショットや言語指示で実行できる汎用ロボット基盤モデルを提案した。

• GenCHiP: 高精度・接触リッチなマニピュレーションタスクのためのロボットポリシーコード生成
  マニピュレーション2024/4/1

  LLMによるロボットポリシーコード生成を、接触力や剛性の制約を考慮した行動空間の再パラメータ化により高精度・接触リッチなタスクへ拡張し、FMBやNISTタスクボードで成功率を大幅に改善した。

• RT-Sketch: 手描きスケッチによる目標条件付き模倣学習
  模倣学習2024/3/1

  手描きスケッチを目標指定に用いる操作ポリシーを提案し、言語や画像条件よりも曖昧さや視覚的妨害に頑健であることを示した。

• PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
  2024/2/1
• AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
  2024/1/1
• Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities
  2023/12/1
• Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
  2023/12/1
• Foundation Models in Robotics: Applications, Challenges, and the Future
  2023/12/1
• SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention
  2023/12/1
• What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
  2023/12/1
• RoboVQA: Multimodal Long-Horizon Reasoning for Robotics
  2023/11/1
• RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
  2023/11/1
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models
  2023/10/1
• Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
  2023/9/1
• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
  2023/7/1
• Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
  2023/5/1
• Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
  2023/3/1
• Open-World Object Manipulation using Pre-trained Vision-Language Models
  2023/3/1
• PaLM-E: An Embodied Multimodal Language Model
  2023/3/1
• Scaling Robot Learning with Semantically Imagined Experience
  2023/2/1
• RT-1: Robotics Transformer for Real-World Control at Scale
  2022/12/1
• Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models
  2022/11/1
• Code as Policies: Language Model Programs for Embodied Control
  2022/9/1
• Offline Reinforcement Learning at Multiple Frequencies
  2022/7/1
• Inner Monologue: Embodied Reasoning through Planning with Language Models
  2022/7/1
• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
  2022/4/1
• Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
  2022/3/1
• How to Leverage Unlabeled Data in Offline Reinforcement Learning
  2022/2/1
• Autonomous Reinforcement Learning: Formalism and Benchmarking
  2021/12/1
• AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale
  2021/11/1
• Conservative Data Sharing for Multi-Task Offline Reinforcement Learning
  2021/9/1
• Autonomous Reinforcement Learning via Subgoal Curricula
  2021/7/1
• Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
  2021/4/1
• MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
  2021/4/1
• Confidence-rich grid mapping
  2020/6/1
• Modeling Long-horizon Tasks as Sequential Interaction Landscapes
  2020/6/1
• Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning
  2020/4/1
• Thinking While Moving: Deep Reinforcement Learning with Concurrent Control
  2020/4/1
• Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
  2020/4/1
• Gradient Surgery for Multi-Task Learning
  2020/1/1
• Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping
  2019/10/1
• Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning
  2019/10/1
• Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
  2019/10/1
• Dynamics-Aware Unsupervised Discovery of Skills
  2019/7/1
• Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing
  2018/10/1
• Scaling simulation-to-real transfer by learning composable robot skills
  2018/9/1
• Multi-Modal Imitation Learning from Unstructured Demonstrations using Generative Adversarial Nets
  2017/5/1
• Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
  2017/3/1
• Observability-Aware Trajectory Optimization for Self-Calibration with Application to UAVs
  2016/4/1
• Interactive Perception: Leveraging Action in Perception and Perception in Action
  2016/4/1